Ambulances waiting outside a hospital emergency department in Melbourne – a CSIRO big data project has been able to predict inflows on any day with up to 93% accuracy. Photograph: AAP/Julian Smith

Few workplaces might seem more unpredictable in their workload than the emergency department of a major hospital. But even the random circumstances that send patients to the ER start to yield patterns when subjected to new methods of data analysis.

For Dr James Lind, director of access and patient flow at Gold Coast Health, clever analysis of admission records by the CSIRO means he can now predict the Gold Coast hospital’s emergency admissions on any day of the year with an accuracy of up to 93%.

That means the hospital can schedule elective procedures with greater confidence, with less chance that elective beds will need to be cleared to make room for emergencies. That means happier patients, and happier staff.

“There is a cost saving in response to not having reactive staffing patterns and having to put people on overtime shifts,” Dr Lind says. “People like working in a system that is proactive rather than reactive. When we are expecting a patient load everyone knows what their jobs, and you are more efficient with your time.”

The Patient Admission and Prediction Tool (PAPT) developed by the CSIRO is just one example of how public sector organisations are using new techniques in data analytics (also known as big data) to find useful patterns in the vast volumes of data they collect.

Current initiatives include the Australian Taxation Office trawling through records to find evidence of the use of tax havens, and data-matching to identify small online retailers that are not meeting their compliance obligations.

Big data techniques are also used by the Department of Human Services to improve service delivery, including creating more personalised services and detecting fraud and compliance issues.

The volumes of data available for the analysis within the Australian public sector are enormous – the Department of Human Services alone deals with 23.4m active Medicare records, approximately 7.1m Centrelink users and 1.2m child support cases.

In March 2013, the Australian Government Information Management Office launched a centre of excellence in data analytics, headed by the tax office, and numerous state-based big data initiatives are also in development.

According to the global manager for analytics at the analyst firm Gartner, Ian Bertram, the possibilities for use of big data within the public sector are endless.

“There is a whole raft of stuff around transportation, around emergency services, and around health,” Bertram says. “But it is still really the ‘art of the possible’. It is not necessarily the ‘art of execution’ at the moment for much of the public sector.”

Numerous limitations exist, including the availability of funds for new projects, as well as restrictions within and between departments as to how the data they have gathered can be used. In many instances data can only be used for administration of the relevant legislative Acts, and not cross-referenced against data in other departments.

Bertram says another limitation is access to skills. “I don’t know if any public sector has necessarily cracked the nut on attracting the right skills and capabilities,” Bertram says. “The commercial sector has, because they’ve got the dollars to spend.”

Regardless, there is enough activity happening now to suggest that big data initiatives are already producing results for government agencies, particularly for emergency services.

One project for the Department of Justice in Victoria undertaken by the analytics firm Predictive Analytics Group is analysing data from the contact centre and dispatch systems for the Victorian 000 emergency for forecasting purposes.

According to Predictive’s founder and managing director Dr Theo Gazos the project has proven useful beyond its initial brief of simply testing business cases.

“It has become so sophisticated that it actually forecasts the number of full-time equivalents required on the call taking side as well as the dispatch side,” Dr Gazos says.

He says uptake within public sector agencies is constrained by budgets, but once solutions are demonstrated they are readily adopted and expanded.

“Government and the public sector generally is becoming more and more interested in the data analytics and predictive analytics,” Dr Gazos says. “Once you show somebody a solution and they get the intuition behind it, they are sold.”

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